Computer Science ›› 2018, Vol. 45 ›› Issue (3): 218-222, 252.doi: 10.11896/j.issn.1002-137X.2018.03.034

Previous Articles     Next Articles

Friend Recommendation Method Based on Users’ Latent Features in Social Networks

XIAO Ying-yuan and ZHANG Hong-yu   

  • Online:2018-03-15 Published:2018-11-13

Abstract: With the popularity of social networks,such as Facebook,Twitter and Microblog,friend recommendation systems have gradually become an important part of social networks.Friend recommendation systems effectively expand the scale of user’s social circle and improve user’s social experience by actively recommending new potential friends for users,thus receiving widespread attention.However,how to personalize the user’s needs and recommend realfriends to users has been one of the difficulties for personalized friend recommendation.This paper presented a social networking friend recommendation method based on users’ latent features,called SNFRLF.SNFRLF first leverages latent factor model to mine users’ latent features,and then calculates the similarity between users by means of users’ latent features.Finally,the similarity is introduced into the random walk model to get a recommended list.The experimental results show that the proposed method significantly outperforms the existing friend recommendation methods.

Key words: Friend recommendation,Social network,Latent factor model,Random walk

[1] SHIH S Y,LEE M,CHEN C C.An effective friend recommendation method using learning to rank and social influence[C]∥PACIS 2015.2015.
[2] CHEN J,GEYER W,DUGAN C,et al.Make New Friends,but Keep the Old:Recommending People on Social Networking Sites[C]∥Proceedings of the 27th International Conference on Human Factors in Computing Systems.2009:201-210.
[3] MENG X W,LIU S D,ZHANG Y J,et al.Research on Recommender Systems[J].Journal of Software,2015,6(6):1356-1372.(in Chinese) 孟祥武,刘树栋,张玉洁,等.社会化推荐系统研究[J].软件学报,2015,6(6):1356-1372.
[4] MA H,YANG H,LYU M R,et al.SoRec:social recommendation using probabilistic matrix factorization[C]∥Proceedings of the 17th ACM Conference on Information and Knowledge Ma-nagement(CIKM’08).ACM,2008:931-940.
[5] RENDLE S,FREUDENTHALER C,GANTNER Z,et al.BPR:Bayesian personalized ranking from implicit feedback [C]∥Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence(UAI’09).ACM,2009:452-461.
[6] HOFMANN T.Latent SEMANTIC Models for CollaborativeFiltering[J].ACM Transactions on Information Systems,2004,22(1):89-115.
[7] KOREN Y.Factorization meets the neighborhood:a multiface-ted collaborative filtering model[C]∥Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Disco-very and Data Mining.ACM,2008:426-434.
[8] SHEN Y,JIN R.Learning personal+social latent factor model for social recommendation[C]∥Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(KDD’12).ACM,2012:1303-1311.
[9] YE M,LIU X,LEE W C.Exploring social influence for recommendation-a generative model approach[C]∥Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR’12).2012:671-680.
[10] WAN S,LAN Y,GUO J,et al.Informational friend recommendation in social media[C]∥Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR’13).ACM,2013:1045-1048.
[11] CHEN C C,SHIH S Y,MENG L,et al.Who should you follow? Combining learning to rank with social influence for informative friend recommendation[J].Decision Support Systems,2016,90:33-45.
[12] LIBEN-NOWELL D,KLEINBERG J.The link-prediction problem for social networks[J].Journal of the American Society for Information Science and Technology,2007,58(7):1019-1031.
[13] JAMALI M,ESTER M.Trustwalker:a random walk model for combining trust-based and item-based recommendation [C]∥ACM Sigkdd International Conference on Knowledge Discovery &Data Mining.2009:397-406.
[14] LESKOVEC J,HUTTENLOCHER D,KLEINBERG J.Predicting positive and negative links in online social networks[C]∥Proceedings of the 19th International Conference on World Wide Web(WWW’10).ACM,2010:641-650.
[15] DENG S G,HUANG L T,XU G H.Social network-based ser-vice recommendation with trust enhancement[J].Expert Systems with Applications,2014,41(18):8075-8084.
[16] SARUKKAI R R.Link prediction and path analysis usingMarkov chains[J].Computer Networks,2000,33(1-6):377-386.
[17] MASSA P,AVESANI P.Trust-aware recommender systems[C]∥Proceedings of the 2007 ACM Conference on Recommender Systems.2007:17-24.
[18] ARMENTANO M G,GODOY D,AMANDI A.Topology-based recommendation of users in micro-blogging communities[J].Journal of Computer Science and Technology,2012,27(3):624-634.
[19] WANG J,DE VRIES A P,REINDERS M J.Unifying user-based and item-based collaborative filtering approaches by similarity fusion[C]∥Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.ACM,2006:501-508.
[20] CHEN K,CHEN T,ZHENG G,et al.Collaborative personalized tweet recommendation[C]∥Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR’12).ACM,2012:661-670.

No related articles found!
Full text



[1] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75, 88 .
[2] XIA Qing-xun and ZHUANG Yi. Remote Attestation Mechanism Based on Locality Principle[J]. Computer Science, 2018, 45(4): 148 -151, 162 .
[3] LI Bai-shen, LI Ling-zhi, SUN Yong and ZHU Yan-qin. Intranet Defense Algorithm Based on Pseudo Boosting Decision Tree[J]. Computer Science, 2018, 45(4): 157 -162 .
[4] WANG Huan, ZHANG Yun-feng and ZHANG Yan. Rapid Decision Method for Repairing Sequence Based on CFDs[J]. Computer Science, 2018, 45(3): 311 -316 .
[5] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[6] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[7] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[8] LIU Qin. Study on Data Quality Based on Constraint in Computer Forensics[J]. Computer Science, 2018, 45(4): 169 -172 .
[9] ZHONG Fei and YANG Bin. License Plate Detection Based on Principal Component Analysis Network[J]. Computer Science, 2018, 45(3): 268 -273 .
[10] SHI Wen-jun, WU Ji-gang and LUO Yu-chun. Fast and Efficient Scheduling Algorithms for Mobile Cloud Offloading[J]. Computer Science, 2018, 45(4): 94 -99, 116 .